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| Section | Weight | Objectives |
|---|---|---|
| Deploying API Implementations to CloudHub | 11% | - Worker sizing and resource planning - VPC and private space configuration - CloudHub architecture and capabilities - Deployment optimization and scaling |
| Architecting and Deploying API Implementations | 11% | - Networking and security configuration - CI/CD and DevOps integration - High availability and fault tolerance - Runtime architecture and deployment options |
| Establishing Organizational and Platform Foundations | 17% | - Center for Enablement (C4E) operating model - Anypoint Platform architecture and components - Governance and organizational structure - Platform strategy and roadmap definition |
| Applying Integration Patterns | 11% | - Scalability and performance patterns - Error handling and reliability patterns - Event-driven and synchronous integration - Common integration patterns and use cases |
| Explaining Application Network Basics | 11% | - Benefits of modern API design - Core concepts of application networks - API-led connectivity principles |
| Meeting API Quality Goals | 8% | - Performance and latency requirements - Maintainability and testability - Reliability and availability targets - Security and compliance standards |
| Monitoring and Analyzing Application Networks | 8% | - Logging and alerting configuration - Operational visibility and optimization - Analytics and insight generation - Monitoring strategies and tools |
| Designing and Sharing APIs | 11% | - API design standards and best practices - Asset sharing and reuse via Anypoint Exchange - API specification and documentation - API layering: Experience, Process, System APIs |
| Managing APIs | 12% | - Rate limiting and throttling - Versioning and deprecation strategies - API lifecycle management - API policies and security enforcement |
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NEW QUESTION # 89
Which layer in the API-led connectivity focuses on unlocking key systems, legacy systems, data sources etc and exposes the functionality?
Answer: A
Explanation:
Correct Answe r: System Layer
The APIs used in an API-led approach to connectivity fall into three categories:
System APIs - these usually access the core systems of record and provide a means of insulating the user from the complexity or any changes to the underlying systems. Once built, many users, can access data without any need to learn the underlying systems and can reuse these APIs in multiple projects.
Process APIs - These APIs interact with and shape data within a single system or across systems (breaking down data silos) and are created here without a dependence on the source systems from which that data originates, as well as the target channels through which that data is delivered.
Experience APIs - Experience APIs are the means by which data can be reconfigured so that it is most easily consumed by its intended audience, all from a common data source, rather than setting up separate point-to-point integrations for each channel. An Experience API is usually created with API-first design principles where the API is designed for the specific user experience in mind.
NEW QUESTION # 90
An organization wants to make sure only known partners can invoke the organization's APIs. To achieve this security goal, the organization wants to enforce a Client ID Enforcement policy in API Manager so that only registered partner applications can invoke the organization's APIs. In what type of API implementation does MuleSoft recommend adding an API proxy to enforce the Client ID Enforcement policy, rather than embedding the policy directly in the application's JVM?
Answer: B
Explanation:
Correct Answe r: A Non-Mule application
*****************************************
>> All type of Mule applications (Mule 3/ Mule 4/ with APIkit/ with Custom Java Code etc) running on Mule Runtimes support the Embedded Policy Enforcement on them.
>> The only option that cannot have or does not support embedded policy enforcement and must have API Proxy is for Non-Mule Applications.
So, Non-Mule application is the right answer.
NEW QUESTION # 91
Which three tools automate the deployment of Mule applications?
Choose 3 answers
Answer: B,C,E
Explanation:
MuleSoft offers various tools to automate the deployment of Mule applications, which can streamline deployment and management processes. Here's how each tool supports automated deployment:
Runtime Manager:
Anypoint Runtime Manager is MuleSoft's web-based interface that allows users to deploy, manage, and monitor applications directly. It provides deployment automation through its user-friendly interface.
Anypoint Platform CLI:
The Anypoint CLI enables scripting of deployment and management tasks, making it possible to automate deployments via command-line scripts. This tool is ideal for CI/CD pipelines as it integrates with automated processes.
Platform APIs:
MuleSoft's Platform APIs allow programmatic access to deployment functions, enabling integration with external automation tools and CI/CD systems. These APIs facilitate deployment through RESTful calls, which can be automated for continuous delivery.
of Incorrect Options:
Option D (Anypoint Studio) is primarily for development and does not support deployment automation.
Option E (Maven Plugin) can be used for building and deploying Mule applications but isn't classified as a platform tool for deployment.
Option F (API Community Manager) is unrelated to deployment and instead focuses on managing API communities.
Reference
For detailed steps on automating deployments with these tools, refer to MuleSoft documentation on Runtime Manager, CLI, and Platform APIs.
NEW QUESTION # 92
Which statement is true about Spike Control policy and Rate Limiting policy?
Answer: C
Explanation:
Understanding Spike Control and Rate Limiting Policies:
Spike Control Policy: Limits the number of requests processed by the API in a short time to handle sudden bursts of traffic. It does not queue requests but rejects any request that exceeds the allowed burst rate.
Rate Limiting Policy: Sets a limit on the number of requests that an API can handle within a given timeframe. Once the limit is reached, additional requests are rejected.
Evaluating the Options:
Option A: Incorrect. In both Spike Control and Rate Limiting policies, requests are rejected once the limit is reached. Spike Control does not queue requests; it only controls the burst rate by rejecting excessive requests.
Option B (Correct Answer): In a clustered environment, each node independently enforces the Rate Limiting and Spike Control policies, meaning that the limits apply to each node separately. This ensures that each node can control its own resource usage independently within the cluster.
Option C: This is partially correct, as Rate Limiting is often used to protect Experience APIs, but Spike Control could also be useful in limiting resource consumption under high burst conditions.
Option D: Incorrect. Although a contract is required to enforce client-specific policies, Rate Limiting and Spike Control do not require a contract to function for general traffic control.
Conclusion:
Option B is the correct answer because, in a clustered environment, Rate Limiting and Spike Control policies apply separately to each node, helping each instance to manage its own load.
For more information, refer to MuleSoft's documentation on applying Rate Limiting and Spike Control policies in a clustered environment.
NEW QUESTION # 93
What correctly characterizes unit tests of Mule applications?
Answer: A
Explanation:
Correct Answe r: They are typically written using MUnit to run in an embedded Mule runtime that does not require external connectivity.
*****************************************
Below TWO are characteristics of Integration Tests but NOT unit tests:
>> They test the validity of input and output of source and target systems.
>> They must be triggered by an external client tool or event source.
It is NOT TRUE that Unit Tests must be run in a unit testing environment with dedicated Mule runtimes for the environment.
MuleSoft offers MUnit for writing Unit Tests and they run in an embedded Mule Runtime without needing any separate/ dedicated Runtimes to execute them. They also do NOT need any external connectivity as MUnit supports mocking via stubs.
https://dzone.com/articles/munit-framework
NEW QUESTION # 94
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